I should admit up front that I don’t have a scientific answer to this comparison, but I do have a reasonably informed gut feel, at least for the near-term. The reason I ask the question is that automated RTL generation grabs headlines with visions of designing chips through natural language prompts, making design widely accessible.… Read More
Tag: bernard murphy
A Compelling Differentiator in OEM Product Design
Jennifer, an OEM hardware designer, is planning a product around a microcontroller she thinks will meet her needs and wants to supply power from a 3V coin cell battery which she must connect though a boost controller. Jennifer searches a rough description of the part she needs, generating a long list of component manufacturers … Read More
Emulator-Like Simulation Acceleration on GPUs. Innovation in Verification
GPUs have been proposed before to accelerate logic simulation but haven’t quite met the need yet. This is a new attempt based on emulating emulator flows. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and lecturer at Stanford, EE292A) and I continue our series… Read More
Learning from In-House Datasets
At a DAC Accellera panel this year there was some discussion on cross-company collaboration in training. The theory is that more collaboration would mean a larger training set and therefore higher accuracy in GenAI (for example in RTL generation). But semiconductor companies are very protective of their data and reports of copyrighted… Read More
Statically Verifying RTL Connectivity with Synopsys
Many years ago, not long after we first launched SpyGlass, I was looking around for new areas where we could apply static verification methods and was fortunate to meet Ralph Marlett, a guy (now friend) with extensive experience in DFT. Ralph joined us and went on to build the very capable SpyGlass DFT app. So capable that SpyGlass… Read More
From Prompts to Prompt Engineering to Knowing Ourselves
I am on a voyage of discovery through prompting and prompting technologies because these are the critical interfaces between what we want (or roughly imagine we want) from AI, and AI’s ability to deliver. I have seen suggestions that any deficiencies today are a detail that will soon be overcome. I’m not so sure. Yes, prompting technology… Read More
A Remote Touchscreen-like Control Experience for TVs and More
How do you control your smart TV? With a remote control of course, already quite capable since it allows voice commands to find a movie or TV show without needing all that fiddly button-based control and lookup. But there’s a range of things you can’t do that we take for granted on a tablet or phone screen. Point and click on an object,… Read More
Scaling Debug Wisdom with Bronco AI
In the business press today I still find a preference for reporting proof-of-concept accomplishments for AI applications: passing a bar exam with a top grade, finding cancerous tissue in X-rays more accurately than junior radiologists, and so on. Back in the day we knew that a proof-of-concept, however appealing, had to be followed… Read More
Neurosymbolic code generation. Innovation in Verification
Early last year we talked about state space models, a recent advance over large language modeling with some appealing advantages. In this blog we introduce neurosymbolic methods, another advance in foundation technologies, here applied to automated code generation. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano… Read More
Arm Lumex Pushes Further into Standalone GenAI on Mobile
When I first heard about GenAI on mobile platforms – from Arm, Qualcomm and others – I confess I was skeptical. Surely there wouldn’t be enough capacity or performance to deliver more than a proof of concept? But Arm, and I’m sure others, have been working hard to demonstrate this is more than a party trick. It doesn’t hurt that foundation… Read More
